Strategic Planning
The New Consumer Journey: Google → ChatGPT → Amazon
Most product journeys now bounce across open search, a chat assistant to clarify, and a marketplace to check out. Recent studies show AI assistants are rapidly becoming one of the most influential shopping touch points (second only to search engines in some research), and they often hand off to retailer sites or marketplaces for the final purchase.
3 November 2025
15 min read
The New Consumer Journey
1) Start: Google frames the problem
People still kick off on Google to get the landscape, prices, brands, and vocab. SEO remains foundational because search engines are still the top discovery channel, and overall eCommerce traffic is consolidating toward marketplaces-meaning your organic presence shapes which marketplace journey you trigger.
What to do
Own the “category 101” and “best for X” queries with clear comparison content and structured data.
Match SERP intent: quick answers, spec tables, price anchors, shipping promises.
2) Clarify: ChatGPT narrows choices
Shoppers then jump into ChatGPT (or Perplexity, Gemini, Claude) to translate needs into specs (“under £50, ESD-safe, lightweight, next-day delivery”) and ask follow-ups. Multiple sources show assistants are increasingly used for product research and shortlisting; some find AI now the #2 influence after search, and a meaningful share of sessions click through to retailers from AI platforms.
Reality check
Assistant-referred traffic can be mixed in conversion today (some studies find lower immediate purchase rates), but AI-influenced shopping is rising overall and pushes high-intent users onward to carts. Expect variability by category and by how well your content answers the model’s constraints.
What to do
Make products machine-readable, trustable, recommendable: clear attributes, quantified outcomes, proofs (tests, certifications), crawlable FAQs.
Ensure consistent claims across D2C, PR/reviews, and marketplace PDPs so models don’t see conflicts.
3) Convert: Amazon closes the loop
When the shortlist is set, shoppers head to marketplaces (especially Amazon) for availability, delivery speed, price, and easy returns. Marketplaces continue to concentrate eCommerce traffic, and assistants increasingly pass users there.
What to do
Answer assistant-style questions on the PDP (bullets, A+, Q&A) so your page earns recommendations from both AI assistants and Amazon’s own systems.
Tighten images with on-image spec callouts; keep titles/bullets consistent with your site to avoid model confusion.
The tracking problem (for now)
This journey introduces invisible hops:
Assistant sessions often appear as direct or unattributed when they hand off.
Chat completions can launch deep links straight to PDPs, skipping your site.
App-heavy behavior (Amazon/retailer apps) increases the gap between influence and last-click.
What to watch..
Lift in brand queries and marketplace search share after assistant-facing content updates.
Changes in cart-ready traffic patterns (shorter time-to-purchase, fewer pageviews before add-to-cart).
Post-update shifts in review language (models often echo phrasing buyers saw upstream).
Why SEO and Paid Search still matter
SEO wins the first question and supplies authoritative, structured facts that assistants reuse. Search remains the top shopping influence in new data, for now...
Paid search fills gaps on competitive terms and accelerates testing of angles and attributes. With traffic consolidating into marketplaces, using SEM to seed brand recall early increases downstream assistant recommendations and marketplace conversion.
Why appearing correctly in ChatGPT now drives Amazon sales
Assistants are becoming a decision compression layer: they transform messy needs into a confident shortlist and then push users to check out. Multiple studies show growing assistant influence and click-through to shopping destinations.
When your content maps precisely to the constraints buyers ask (materials, compliance, fit, sensitivities, delivery), you are more likely to be cited and clicked. Conversely, missing attributes or conflicting claims get you skipped.
Metrics to align your team and business behind
Share of Model visibility: % of relevant assistant answers that mention or feature your brand (by category prompt set).
Traffic from AI: assistant-referred sessions and their assisted-conversion lift (expect some attribution gaps).
Sell-through / Conversion lift: especially on Amazon—tie PDP content updates to add-to-cart and ordered-items changes post-release. (AI-influenced shopping grew notably in recent periods, even if immediate last-click varies by category.)
How LMO7 helps
AI Search Audit across Google → ChatGPT/Perplexity/Gemini/Claude → Amazon, mapping where you appear, what assistants “say,” and which attributes they’re missing.
Signal Architecture: unify product data, proofs, and FAQs so assistants can reason and cite you confidently.
PDP Answering Sprints: convert buyer prompts into bullets, A+, and Q&A that win both assistant citations and Amazon conversions.
Model Surface Monitoring: track Share of Model visibility and tie fixes to marketplace sell-through.
Bottom line
The journey isn’t linear. It’s search → chat → checkout. SEO primes the funnel, assistants compress the decision, and Amazon converts. If your products are the right answer for people, make them the right answer for models and you’ll win the new path to purchase.
1) Start: Google frames the problem
People still kick off on Google to get the landscape, prices, brands, and vocab. SEO remains foundational because search engines are still the top discovery channel, and overall eCommerce traffic is consolidating toward marketplaces-meaning your organic presence shapes which marketplace journey you trigger.
What to do
Own the “category 101” and “best for X” queries with clear comparison content and structured data.
Match SERP intent: quick answers, spec tables, price anchors, shipping promises.
2) Clarify: ChatGPT narrows choices
Shoppers then jump into ChatGPT (or Perplexity, Gemini, Claude) to translate needs into specs (“under £50, ESD-safe, lightweight, next-day delivery”) and ask follow-ups. Multiple sources show assistants are increasingly used for product research and shortlisting; some find AI now the #2 influence after search, and a meaningful share of sessions click through to retailers from AI platforms.
Reality check
Assistant-referred traffic can be mixed in conversion today (some studies find lower immediate purchase rates), but AI-influenced shopping is rising overall and pushes high-intent users onward to carts. Expect variability by category and by how well your content answers the model’s constraints.
What to do
Make products machine-readable, trustable, recommendable: clear attributes, quantified outcomes, proofs (tests, certifications), crawlable FAQs.
Ensure consistent claims across D2C, PR/reviews, and marketplace PDPs so models don’t see conflicts.
3) Convert: Amazon closes the loop
When the shortlist is set, shoppers head to marketplaces (especially Amazon) for availability, delivery speed, price, and easy returns. Marketplaces continue to concentrate eCommerce traffic, and assistants increasingly pass users there.
What to do
Answer assistant-style questions on the PDP (bullets, A+, Q&A) so your page earns recommendations from both AI assistants and Amazon’s own systems.
Tighten images with on-image spec callouts; keep titles/bullets consistent with your site to avoid model confusion.
The tracking problem (for now)
This journey introduces invisible hops:
Assistant sessions often appear as direct or unattributed when they hand off.
Chat completions can launch deep links straight to PDPs, skipping your site.
App-heavy behavior (Amazon/retailer apps) increases the gap between influence and last-click.
What to watch..
Lift in brand queries and marketplace search share after assistant-facing content updates.
Changes in cart-ready traffic patterns (shorter time-to-purchase, fewer pageviews before add-to-cart).
Post-update shifts in review language (models often echo phrasing buyers saw upstream).
Why SEO and Paid Search still matter
SEO wins the first question and supplies authoritative, structured facts that assistants reuse. Search remains the top shopping influence in new data, for now...
Paid search fills gaps on competitive terms and accelerates testing of angles and attributes. With traffic consolidating into marketplaces, using SEM to seed brand recall early increases downstream assistant recommendations and marketplace conversion.
Why appearing correctly in ChatGPT now drives Amazon sales
Assistants are becoming a decision compression layer: they transform messy needs into a confident shortlist and then push users to check out. Multiple studies show growing assistant influence and click-through to shopping destinations.
When your content maps precisely to the constraints buyers ask (materials, compliance, fit, sensitivities, delivery), you are more likely to be cited and clicked. Conversely, missing attributes or conflicting claims get you skipped.
Metrics to align your team and business behind
Share of Model visibility: % of relevant assistant answers that mention or feature your brand (by category prompt set).
Traffic from AI: assistant-referred sessions and their assisted-conversion lift (expect some attribution gaps).
Sell-through / Conversion lift: especially on Amazon—tie PDP content updates to add-to-cart and ordered-items changes post-release. (AI-influenced shopping grew notably in recent periods, even if immediate last-click varies by category.)
How LMO7 helps
AI Search Audit across Google → ChatGPT/Perplexity/Gemini/Claude → Amazon, mapping where you appear, what assistants “say,” and which attributes they’re missing.
Signal Architecture: unify product data, proofs, and FAQs so assistants can reason and cite you confidently.
PDP Answering Sprints: convert buyer prompts into bullets, A+, and Q&A that win both assistant citations and Amazon conversions.
Model Surface Monitoring: track Share of Model visibility and tie fixes to marketplace sell-through.
Bottom line
The journey isn’t linear. It’s search → chat → checkout. SEO primes the funnel, assistants compress the decision, and Amazon converts. If your products are the right answer for people, make them the right answer for models and you’ll win the new path to purchase.